alexa An Improved Compression Scheme Using Particle Swarm Op
ISSN ONLINE(2278-8875) PRINT (2320-3765)

International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering
Open Access

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Research Article

An Improved Compression Scheme Using Particle Swarm Optimised Neural Network for ECG Signals

M.J.Jayashree1, Dr.A.Sukesh Kumar2
  1. Associate Professor, Dept. of ECE, Mar Baselios College of Engineering and Technology, Mar Ivanios Vidya Nagar, Nalanchira, Thiruvananthapuram, Kerala, India
  2. Retd. Principal(Govt. Engineering College), TC 15/223, USRA – 26, US Road, Vellayambalam, 695010, Thiruvananthapuram, Kerala, India
Corresponding Author: SHARMA VIVEK, E-mail: [email protected]
Related article at Pubmed, Scholar Google


The emergence of artificial neural networks in signal processing has led to improvements in signal compression. In this paper a comparison of ECG signal compression using Multi Layer Perceptron(MLP) neural network and Particle Swarm Optimisation(PSO) is made. For this different back propagation artificial networks are used as compressor and decompressor. Particle swarm optimisation (PSO) is used for optimising the learning rate and momentum. The proposed algorithm yields minimum mean square error for the ECG signals from MIT-BIH arrhythmia data base.


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